This invention relates to moisture sensors and more specifically, to a manner of using an aluminum oxide moisture sensor that improves the speed of response of the sensor.
An aluminum oxide moisture sensor (or hygrometer) uses aluminum oxide and a thin film of noble metal to form what is essentially a capacitor. The water molecules in the test medium are absorbed and electrical impedance is measured. The capacitor's value is then translated and displayed as a value of, for example, PPM.
More specifically, a typical aluminum oxide sensor is comprised of an aluminum base that is anodized to produce a thin layer of active aluminum oxide. A thin coating of noble metal, for example, gold, is evaporated over this structure, and the two metal layers form the electrodes of the capacitor, while the aluminum oxide serves as the dielectric, sandwiched between the electrodes.
When the sensor is exposed to moisture, water vapor is rapidly transported through the exposed (positive) electrode layer where the polar water molecules form weak hydrogen bonds at the oxide surfaces. Adsorption causes changes in the dielectric constant and resistivity of the oxide layers. Thus, a measure of the sensor conductance is a measure of moisture loading on the aluminum oxide dielectric and is proportional to the moisture concentration in the sample gas.
Activated aluminum oxide is widely used as the dielectric since its adsorption capacity or loading is a function of humidity level of the surrounding gas, temperature, and the oxide layer's thickness and porosity (exposed surface area). These factors will also determine the rate of adsorption.
The properties of hygroscopic sensor materials usually exhibit large temperature dependence. To minimize this effect, sensors often are bonded to an additional substrate containing a heater and RTD assembly for stable temperature control.
It is well known, however, that aluminum oxide moisture sensors exhibit very slow response at trace (PPBV) moisture levels. In addition, measurement methods currently in use rely on equilibrium values, which require several hours to reach. Over time, these measurements also show considerable offset drift, requiring frequent recalibration of the sensors. Past efforts to improve performance have used special algorithms to anticipate sensor response. This method relies on hard-to-measure variables, however, that may vary widely between applications. Without good knowledge of application properties, this factor greatly limits sensor performance.